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Proceedings Paper

The segmentation of the CT image based on k clustering and graph-cut
Author(s): Yuke Chen; Xiaoming Wu; Rongqian Yang; Shanxin Ou; Ken Cai; Hai Chen
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Paper Abstract

Computed tomography angiography (CTA) is widely used to assess heart disease, like coronary artery disease. In order to complete the auto-segmentation of cardiac image of dual-source CT (DSCT) and extract the structure of heart accurately, this paper proposes a hybrid segmentation method based on k clustering and Graph-Cuts (GC). It identifies the initial label of pixels by this method. Based on this, it creates the energy function of the label with the knowledge of anatomic construction of heart and constructs the network diagram. Finally, it minimizes the energy function by the method of max-flow/min-cut theorem and picks up region of interest. The experiment results indicate that the robust, accurate segmentation of the cardiac DSCT image can be realized by combining Graph-Cut and k clustering algorithm.

Paper Details

Date Published: 5 December 2011
PDF: 8 pages
Proc. SPIE 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing, 80050V (5 December 2011); doi: 10.1117/12.902418
Show Author Affiliations
Yuke Chen, South China Univ. of Technology (China)
General Hospital of Guangzhou Military Command of PLA (China)
Xiaoming Wu, South China Univ. of Technology (China)
Rongqian Yang, South China Univ. of Technology (China)
Shanxin Ou, General Hospital of Guangzhou Military Command of PLA (China)
Ken Cai, South China Univ. of Technology (China)
Hai Chen, General Hospital of Guangzhou Military Command of PLA (China)


Published in SPIE Proceedings Vol. 8005:
MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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